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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/prepare-for-dp-100-design-a-data-science-solution-on-azure
课程评论：没有评论
课程名称：准备DP-100：Microsoft Azure上的数据科学考试 课程概述：微软认证为您提供职业优势，证明您掌握了数字和云业务技能。在本课程中，您将为参加DP-100 Azure数据科学家助理认证考试做好准备。您将复习如何在Azure上规划和创建适合数据科学工作负载的工作环境，进行数据实验，以及训练预测模型。此外，您还将回顾如何管理、优化并将机器学习模型部署到生产环境中。 课程设置包括与DP-100考试主要主题对应的练习考试，以确保您为认证成功做好充分准备。您将详细了解微软认证项目及其在职业生涯中的下一步发展。此外，您还将获取一些技巧、测试策略、有用的资源以及如何注册DP-100监考考试的信息。完成本课程后，您将准备好注册并参加DP-100考试。 此课程为五门课程项目中的第五门，旨在帮助您准备DP-100：在Azure上设计和实施数据科学解决方案的认证考试。该认证考试是证明您在云规模上使用Azure机器学习操作机器学习解决方案的知识和专业技能的机会。本专业化课程教您如何利用现有的Python和机器学习知识，管理数据摄取和准备、模型训练和部署，以及机器学习解决方案的监控。 本专业化课程面向已有Python和机器学习框架（如Scikit-Learn、PyTorch和Tensorflow）知识的数据科学家，旨在帮助他们在云中构建和操作机器学习解决方案。学员将学习如何在Microsoft Azure中管理机器学习的资源；运行实验和训练模型；部署和操作机器学习解决方案；以及实施负责任的机器学习。同时，他们还将学习如何使用Azure Databricks进行数据的探索、准备和建模；并将Databricks机器学习流程与Azure机器学习集成。 课程大纲： - 了解微软认证路径、基于角色的认证及与认证相关的职位和职业。 - 回顾微软Azure数据科学家助理专业化的各个课程，确保自己掌握核心概念。 - 完成最终练习考试，了解考试内容的重要性及技能测评方式，并获取如何预定认证考试的信息。 通过该课程的学习，您将能有效提升自己在Azure环境下数据科学和机器学习领域的能力，为未来的职场挑战做好全面准备。
Name:Prepare for the DP-100: Designing and implementing a Data Science Solution on Azure Exam
Description:After completing this module, you will have an understanding of Microsoft certification pathways, role-based certifications and jobs and careers associated with certification. You will also find out how to prepare for the proctored exam, including the topics covered in the exam, how the exam is administered and exam strategy, tips and tricks.
Name:Exam preparation - Course 1
Description:In this module you’ll review Course 1 of the Microsoft Azure Data Scientist Associate specialization.
Name:Exam preparation - Course 2
Description:In this module you’ll review Course 2 of the Microsoft Azure Data Scientist Associate specialization.
Name:Exam preparation - Course 3
Description:In this module you’ll review Course 3 of the Microsoft Azure Data Scientist Associate specialization.
Name:Exam preparation - Course 4
Description:In this module you’ll review Course 4 of the Microsoft Azure Data Scientist Associate specialization.
Name:Final Practice Exam
Description:In this module, you will find out how the core concepts are weighted and skills are measured, before taking the full practice exam. Following this you will find out how you can book your certification exam.
Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses. In this course, you will prepare to take the DP-100 Azure Data Scientist Associate certification exam. You will refresh your knowledge of how to plan and create a suitable working environment for data science workloads on Azure, run data experiments, and train predictive models. In addition, you will recap on how to manage, optimize, and deploy machine learning models into production. You will test your knowledge in a practice exam mapped to all the main topics covered in the DP-100 exam, ensuring you’re well prepared for certification success. You will also get a more detailed overview of the Microsoft certification program and where you can go next in your career. You’ll also get tips and tricks, testing strategies, useful resources, and information on how to sign up for the DP-100 proctored exam. By the end of this course, you will be ready to sign-up for and take the DP-100 exam. This is the fifth course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azure certification exam. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Each course teaches you the concepts and skills that are measured by the exam. This Specialization is intended for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. It teaches data scientists how to create end-to-end solutions in Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions, and implement responsible machine learning. They will also learn to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.
